Fraud-signal scoring
30–50% ↓
false positives
Combine transaction features and free-text narratives to score fraud risk. Outputs explainable rationale alongside the score, so reviewers can disposition faster.
Fintech
AI for fintechs that need to ship in regulated waters.
AISD builds AI agents and software for fintechs — fraud-signal scoring, KYC and document processing, underwriting copilots, customer-service deflection, and compliance monitoring. SOC 2 Type II audit in progress, on-prem deployment available.
6 proven use cases · 4–9 mo typical payback · VPC & on-prem available
Use cases
Six places AI agents earn their keep at a fintech.
Document processing
40–70%
operations time saved
KYC docs, loan files, ID verification, demand letters — extracted into structured fields with audit trails. Validates against business rules; routes exceptions to humans.
Customer-service deflection
25–40%
auto-resolution
Resolve balance, transfer, dispute, and account-question queries without human handoff. Hand off cleanly when the question requires judgment.
Underwriting copilots
2–3×
review throughput
Surface risk signals, comparable cases, and policy precedents during quote review. Underwriter stays in control; the copilot does the legwork.
Compliance monitoring
24/7
anomaly detection
Flag transaction anomalies, draft SARs from structured inputs, and surface coverage gaps. Logs every decision for examiner review.
Account-opening agents
5–10× faster
onboarding
Conversational onboarding that collects documents, validates against KYC requirements, and provisions accounts — all auditable and compliant.
Compliance & data handling
Built for the constraints fintech actually has.
PCI, SOC 2, banking regulators, state DOIs — the constraints that make fintech AI different from generic enterprise AI. We build for them, not around them.
PII / PCI redaction at the boundary
Agents see only the fields they need. PANs, SSNs, and other restricted data are redacted before they reach the model.
Audit-grade logging
Every model call is logged with inputs, outputs, and decision rationale — searchable and exportable for regulator review.
VPC / on-prem deployment
When state regulators or bank policy require, we run open-weight models on dedicated infrastructure with no data leaving your perimeter.
Human-in-the-loop on financial decisions
Account closures, large refunds, and credit decisions are AI-assisted, not AI-made. The agent surfaces evidence; the human decides.
Featured case study · Fintech MVP
Fintech MVP shipped at 60% lower cost, 2× faster.
Original quote was $150K–$200K and 4 months. We delivered for $80K in half the time, with production-grade architecture.
Read the full case study →Outcome
60%
cost reduction vs. original quote
Services for fintech
Fintech-aligned case studies
Frequently asked
Common questions.
What AI use cases work for fintechs today?
Five proven patterns. Fraud-signal scoring (combine transaction features + narratives, output explainable risk scores). Document processing (KYC, loan docs, ID verification → structured fields with audit trails). Customer-service deflection (resolve balance / transfer / dispute queries without human handoff). Underwriting copilots (surface comparable cases and risk signals to underwriters during review). Compliance monitoring (flag anomalies, auto-draft SARs). Highest-ROI is whichever has the highest volume + structured outputs.
How does AISD handle PCI / SOC 2 / banking-regulator constraints?
Three patterns. PII / PCI redaction at the boundary — agents see only the fields they need; PANs and SSNs never reach the model. Audit-grade logging — every decision logged with rationale, exportable for examiners. VPC / on-prem deployment when state regulators or bank policy require it; we run open-weight models on dedicated infra with no data leaving your perimeter. SOC 2 Type II audit in progress; HIPAA-aligned engagements available.
What's typical ROI for an AI build at a fintech?
Outcomes by use case. Fraud scoring: 30–50% reduction in false positives + faster reviewer disposition. Document processing: 40–70% reduction in operations review time. Customer-service deflection: 25–40% auto-resolve. Build cost typically pays back in 4–9 months on the volume use cases. We recommend starting with a 2-week discovery sprint scoped to a single use case before committing to a full build.
How long does it take to build a production AI agent?
Working prototype: 2 weeks. Production-grade agent (with eval harness, guardrails, observability, and a runbook): 6–10 weeks. The prototype-to-production gap is where most projects fail — the prototype handles the happy path; production has to handle the long tail.
What does it cost to build an AI agent?
A production AI agent at AISD typically costs $40,000–$150,000 depending on complexity. Drivers: number of integrated systems, evaluation rigor required, compliance overhead, and ongoing operational scope. Prototypes alone are cheaper ($10k–$25k) but rarely worth it without a path to production.
How do you ensure AI features are reliable in production?
Five layers: an offline eval harness with golden test sets run on every PR; confidence thresholds and structured-output validation that gate downstream side effects; runtime observability — every model call logged with inputs, outputs, latency, cost; circuit breakers and deterministic fallbacks for every model dependency; and a weekly review ritual where prompt regressions get caught before they become incidents.
How is AISD different from a typical software development agency?
Three differences. First, every AISD engineer is senior — minimum 5 years building production software, with shipped AI features. Second, we publish hourly engagement bands and project ranges so you know roughly what an engagement costs before the first call. Third, we take fewer concurrent projects so a partner stays close to delivery.
Is AISD SOC 2 / GDPR / HIPAA compliant?
GDPR: yes — we handle EU personal data under standard data-processing agreements and apply data-minimization patterns (redaction at source, retention windows, right-to-erasure tooling). SOC 2: Type II audit in progress. HIPAA: we deliver HIPAA-aligned engagements (BAAs available, PHI handling patterns established) but do not yet hold a third-party HIPAA attestation. We will not claim certifications we don't hold.